对焦虑进行对话的数字程序的可接受性:对用户观点的混合方法研究
Pearla Papiernik1, Sylwia Dzula1, Marta Zimanyi2
1ieso Digital Health, The Jeffreys Building, Cowley Road, Cambridge, GB.
JMIR human factors
|August 18, 2025
概括
使用人工智能聊天机器人的数字心理健康干预 (DMHI) 是可以接受的,并且对普遍焦虑有吸引力. 然而,个性化需要进一步发展,以获得最佳的患者体验.
科学领域:
- 数字健康数字健康
- 人工智能在心理健康中的作用
- 人与计算机的交互
背景情况:
- 全球焦虑和抑郁率的上升使传统的心理健康服务受到压力.
- 数字心理健康干预 (DMHI) 提供可扩展的解决方案,但面临着参与挑战.
- 人工智能驱动的对话代理显示出增强DMHIs的希望,但它们的可接受性仍在调查中.
研究的目的:
- 评估对话性代理主导的DMHI的可接受性,参与性和可用性,并对通用焦虑进行人类支持.
- 用混合方法探索患者对这个数字心理健康计划的期望和经验.
主要方法:
- 采用混合方法的方法,299名参与者参加了长达9周的DMHI.
- 干预后收集的定量数据包括参与 (UES),可用性 (SUS) 和可接受性 (SUTAQ) 的验证措施.
- 从干预前和干预后的采访中获得的定性数据 (N=21和N=16,分别) 被主题分析以了解用户体验.
主要成果:
- 参与者报告了高参与度 (平均UES=3.7) 和易用性 (SUS=78.6),发现该计划是有益的和可访问的.
- DMHI提高了护理准入和满意度 (平均 SUTAQ=4.3-4.9),满足了大多数用户的需求.
- 关键的可接受性主题包括可访问的护理,有效的解决方案,个性化,指导控制和人类支持,尽管参与者希望更多的个性化.
结论:
- 纳入以患者为中心的设计因素的DMHIs对于全球精神卫生保健的影响至关重要.
- 这项研究证实了结构化,人工智能驱动的DMHI的可接受性,并支持人类对一般性焦虑的治疗.
- 优化个性化和利用安全的人工智能集成的分层人力支持可以显著提高患者体验和DMHIs的现实世界的有效性.
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